Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace
from plotly.offline import init_notebook_mode
import pandas as pd
import numpy as np
import plotly.io as pio
import plotly.express as px
import plotly.graph_objects as go
import json
import itertools
import geopandas as gpd
init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
#load data
df = px.data.gapminder()
df.head()
| country | continent | year | lifeExp | pop | gdpPercap | iso_alpha | iso_num | |
|---|---|---|---|---|---|---|---|---|
| 0 | Afghanistan | Asia | 1952 | 28.801 | 8425333 | 779.445314 | AFG | 4 |
| 1 | Afghanistan | Asia | 1957 | 30.332 | 9240934 | 820.853030 | AFG | 4 |
| 2 | Afghanistan | Asia | 1962 | 31.997 | 10267083 | 853.100710 | AFG | 4 |
| 3 | Afghanistan | Asia | 1967 | 34.020 | 11537966 | 836.197138 | AFG | 4 |
| 4 | Afghanistan | Asia | 1972 | 36.088 | 13079460 | 739.981106 | AFG | 4 |
Recreate the barplot below that shows the population of different continents for the year 2007.
Hints:
df = px.data.gapminder()
df_2007 = df.query("year==2007")
df_2007_new = df_2007.groupby('continent').sum()
fig = px.bar(df_2007_new, x="pop", y=df_2007_new.index, orientation='h',
color=df_2007_new.index,)
fig.show()
df = px.data.gapminder()
df_2007 = df.query("year==2007")
df_2007_new = df_2007.groupby('continent').sum()
fig = px.bar(df_2007_new, x="pop", y=df_2007_new.index, orientation='h',
color=df_2007_new.index,)
fig.update_yaxes(categoryorder='mean ascending')
fig.show()
Add text to each bar that represents the population
df = px.data.gapminder()
df_2007 = df.query("year==2007")
df_2007_new = df_2007.groupby('continent').sum()
fig = px.bar(df_2007_new, x="pop", y=df_2007_new.index, orientation='h', text_auto=True,
color=df_2007_new.index,)
fig.update_yaxes(categoryorder='mean ascending')
fig.show()
Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years
df_world = px.data.gapminder()
df = px.data.gapminder()
fig = px.histogram(df_world, y="continent", x="pop", orientation= "h",
animation_frame="year",
range_x=[0,4000000000],
color="continent",)
fig.update_yaxes(categoryorder='sum ascending')
fig.show()
Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years
df = px.data.gapminder()
fig = px.bar(df, x="pop", y='country', orientation='h', animation_frame="year", animation_group="country",
color='country',)
fig.update_yaxes(categoryorder='sum ascending')
fig.update_layout(showlegend=False)
fig.show()
Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation
df = px.data.gapminder()
fig = px.bar(df, x="pop", y='country', orientation='h', animation_frame="year", animation_group="country",
color='country', height=1000,)
fig.update_yaxes(categoryorder='sum ascending')
fig.update_layout(showlegend=False)
fig.show()
df = px.data.gapminder()
fig = px.bar(df, x="pop", y='country', orientation='h', animation_frame="year", animation_group="country",
color='country',)
fig.update_yaxes(range = [132,142], categoryorder='sum ascending')
fig.update_layout(showlegend=False)
fig.show()